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Record W2332395064 · doi:10.1021/nn203438u

Colloidal Quantum Dot Photovoltaics: A Path Forward

2011· article· en· W2332395064 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACS Nano · 2011
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Toronto
FundersKing Abdullah University of Science and Technology
KeywordsPhotovoltaicsQuantum dotPhotovoltaic systemNanotechnologyOptoelectronicsMaterials scienceMultiple exciton generationBand gapEngineering physicsElectronicsPhysicsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Colloidal quantum dots (CQDs) offer a path toward high-efficiency photovoltaics based on low-cost materials and processes. Spectral tunability via the quantum size effect facilitates absorption of specific wavelengths from across the sun's broad spectrum. CQD materials' ease of processing derives from their synthesis, storage, and processing in solution. Rapid advances have brought colloidal quantum dot photovoltaic solar power conversion efficiencies of 6% in the latest reports. These achievements represent important first steps toward commercially compelling performance. Here we review advances in device architecture and materials science. We diagnose the principal phenomenon-electronic states within the CQD film band gap that limit both current and voltage in devices-that must be cured for CQD PV devices to fulfill their promise. We close with a prescription, expressed as bounds on the density and energy of electronic states within the CQD film band gap, that should allow device efficiencies to rise to those required for the future of the solar energy field.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.227
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it